深度学习超级采样(Deep Learning Super Sampling,DLSS)是Nvidia开发的一种图像缩放技术,可实时用于视频游戏中,這種技術利用深度学习将较低解析度的图像缩放為更高解析度的图像,以便在更高解析度的计算机显示器上显示[1]。
Nvidia在2018年9月推出NVIDIA GeForce 20系列GPU时,將DLSS作為賣點進行宣傳[2]。当时,DLSS的效果仅限于少数几款视频游戏(如《战地5》和《戰慄深隧:流亡》) [3] [4]。 2020年4月,Nvidia推出DLSS 2.0,该版本的DLSS适用于《控制》和《德軍總部:新血脈》等游戏[2] [5]。
DLSS 3.0于2022年10月发布。DLSS 3.5版本于2023年8月22日发布,《心灵杀手2》、《赛博朋克2077》等将成为应用DLSS 3.5技术的首批游戏。[6][7][8]
Deep learning super sampling uses artificial intelligence and machine learning to produce an image that looks like a higher-resolution image, without the rendering overhead. Nvidia’s algorithm learns from tens of thousands of rendered sequences of images that were created using a supercomputer. That trains the algorithm to be able to produce similarly beautiful images, but without requiring the graphics card to work as hard to do it.
Recently, two big titles received NVIDIA DLSS support, namely Metro Exodus and Battlefield V. Both these games come with NVIDIA’s DXR (DirectX Raytracing) implentation that at the moment is only supported by the GeForce RTX cards. DLSS makes these games playable at higher resolutions with much better frame rates, although there is a notable decrease in image sharpness. Now, AMD has taken a jab at DLSS, saying that traditional AA methods like SMAA and TAA “offer superior combinations of image quality and performance.”
The benefit for most people is that, generally, DLSS comes with a sizeable FPS improvement. How much varies from game to game. In Metro Exodus, the FPS jump was barely there and certainly not worth the bizarre hit to image quality.
“The original DLSS required training the AI network for each new game. DLSS 2.0 trains using non-game-specific content, delivering a generalized network that works across games. This means faster game integrations, and ultimately more DLSS games.”